Variables predicting teachers' technological acceptance

Since technology becomes an inevitable part of society, it is important to determine the level of use and acceptance of technology by individuals. There are technology acceptance models to understand individuals' technology acceptance behavior. However, there are also models to understand teachers' technological acceptance like Ursavaş, Şahin, and Mcilroy's (2014) model. It is a collaborative model using planned behavior theory, reasoned behavior theory, technological acceptance model, diffusion of innovation theory, detailed planned behavior theory, social cognitive theory, and motivation theory. The related model consists of 11 dimensions including perceived usefulness, perceived ease of use, perceived fun, anxiety, behavioral intention, compatibility, technological complexity, subjective norm, facilitating situations, attitude towards use, and self-efficacy to measure teachers' technological acceptance. It is crucial to determine the technological acceptance of in-service teachers, to use technology effectively in educational environments, and to identify the facilitators and obstacles related to this process. This study determines some variables that predict secondary school teachers' technology acceptance. Demographic variables such as gender, age and years of service, information technology literacy, and information technology usage levels according to their perceptions are considered predictive variables based on the literature. This is a descriptive study. Data were collected by the stratified proportional sampling of 398 secondary school teachers working in 36 secondary schools in Aydın. Three data collection tools were used in the study. These tools are the technology acceptance scale (37 items) (Ursavaş, Şahin, & Mcilroy, 2014), the information technology literacy scale (17 items) (Kolburan-Geçer & Dağ, 2010), and the information form for determining teachers levels of information technology use (Rieber et al. Welliver, 1989). Data analysis was carried out in the SPSS program. The following findings were obtained by simple linear regression analysis. According to the results of the research, gender and age variables contribute significantly to the prediction of technology acceptance in the dimensions of anxiety, subjective norm and perceived usefulness. The service year variable, on the other hand, makes a significant contribution only in the perceived usefulness dimension. The dimensions of information literacy, internet literacy and computer literacy generally contribute significantly to predicting technology acceptance. Their perceptions of technology usage level contributes significantly to the dimensions of perceived ease of use, perceived fun, self-efficacy, technological complexity and anxiety; does not contribute significantly to any other dimensions.